The results show a large overlap of the genetic makeup associated with functional connectivity across brain networks but also identify network specific signals, suggesting a potential genetic stratification between cognitive and sensory-motor networks.
Abstract
Previous GWAS of brain’s connectivity have been challenged by the difficulty of best representing the complexity of this phenotype. Here we report the results from a multivariate GWAS approach that allows for a better representation of this complexity, while boosting statistical power. This strategy notably increases the detection of significant signals to 114 independent SNPs, pointing at 315 candidate genes. Our results show a large overlap of the genetic makeup associated with functional connectivity across brain networks but also identify network specific signals, suggesting a potential genetic stratification between cognitive and sensory-motor networks. We also identify a large genetic overlap between functional connectivity and risk for neuropsychiatric disorders, suggesting that regions of the genome important for neuronal communication are enriched for neuropsychiatric risk SNPs. The work presented here expands our understanding of the common allele architecture of brain connectivity, as well as provides novel targets to functional genomics research. This study identified 114 independent SNPs (315 candidate genes) associated with brain’s functional connectivity, showing a large genetic commonality affecting connectivity across different brain networks and with several neuropsychiatric conditions.
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